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概要と使いどころ
Inspect a mathematical-modeling workspace, evaluate lean or submission gates per subquestion, update machine-readable manifests, classify change impact, and route one next action without duplicating downstream work.
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Map contest attachments to subquestions, audit and clean raw data, and emit one reusable data profile with quality, coverage, imbalance, concentration, and method-readiness evidence for downstream risk screening.
日本語の概要は準備中です。原文の説明を表示しています。
Runtime API: Context, Device, Stream, buffers, images, ray tracing, and rasterization.
日本語の概要は準備中です。原文の説明を表示しています。
Physics-based animation library combining React Spring (spring dynamics, gesture integration, 60fps animations) and Popmotion (low-level composable animation utilities, reactive streams). Use when building fluid, natural-feeling UI animations, gesture-driven interfaces, physics simulations, or spring-loaded interactions. Triggers on tasks involving React Spring hooks, spring physics, inertia scrolling, physics-based motion, animation composition, or natural UI movements. Alternative physics approach to motion-framer for more physically accurate animations.
日本語の概要は準備中です。原文の説明を表示しています。
Use when updating this codex-app Linux port from the latest upstream Codex Mac DMG, preserving local Linux patches, installing the refreshed desktop app, and publishing the tag-driven Linux release artifacts.
日本語の概要は準備中です。原文の説明を表示しています。
Use when an Unreal Engine 5.8 project misses its frame rate or stutters: "optimize to 60 fps", "we run at 38 fps", CPU or GPU bound, game or render thread too long, hitches, traversal or shader stutter (PSO), GC spikes, camera-cut spikes, Lumen, Nanite, VSM, ray tracing, foliage, crowds or Niagara too expensive, async compute, stat unit, ProfileGPU, Unreal Insights, TraceQuery, snapshothitches, scalability and device profiles, dynamic resolution and TSR, streaming budgets, or proving a fix with before and after captures.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building a Unity 6.3 level or open world: terrain from code or heightmaps, procedural islands, erosion, splat and foliage rules, trees and grass, ProBuilder graybox, level gym, modular kit and prefab placement, set dressing, landmarks and player guidance, the island's edge, spline roads, WFC, fog, additive scene streaming, or a world that hitches, pops in, leaks memory or runs slow on mobile. Keywords: Terrain, TerrainData, ProBuilder, blockout, graybox, modular kit, NavMesh, LoadSceneAsync, open world.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building 3D levels and worlds in Godot 4.7: third-person or FPS controller, player stuck on stairs, spring arm camera clipping, blockout with CSG, GridMap and MeshLibrary, terrain (heightmap, HeightMapShape3D, Terrain3D regions, textures, painting), scattering trees with MultiMesh, streaming a big world, procedural meshes with SurfaceTool, Jolt physics settings, importing GLB or glTF from Blender or AI generators (Scenario, Tripo, Meshy, Hitem3D), import scripts, name suffixes, model facing, collision generation, LODs.
日本語の概要は準備中です。原文の説明を表示しています。
Use when making or fixing real-time VFX in Unity 6.3: explosions, fireballs, projectiles with muzzle, trail and impact, spells, slashes, shockwaves, smoke, sparks, Particle System (Shuriken) or VFX Graph ('VFX Graph explosion', 'particles look bad', 'effect kills fps on mobile', 'too much overdraw'), mesh effects with scrolling textures, an uber VFX shader with LUT ramps, Custom Data and custom vertex streams, flipbooks and VFX textures, pink particles after URP upgrade, VFX budgets and readability.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building or fixing an Unreal Engine 5 level or open world: World Partition, OFPA, Data Layers, Level Instances, Packed Level Actors, HLOD, landscape size, heightmap import or clipping, edit layers, terrain material rules, foliage and grass, a PCG forest or rock scatter, runtime GPU grass, Nanite and tessellation choices, modular kits, a river or village, streaming pop-in, cells not loading, landscape black spots, "PCG shows nothing in the editor", or a world too heavy to hand to lighting.
日本語の概要は準備中です。原文の説明を表示しています。
Capture a 2-3 line pitch from the user, draft a product overview (PRD.md) and a technical design (ARCHITECTURE.md) for a third-party `.ppmplugin` native control, then walk through every operation's iOS + Android implementation strategy with opinionated recommendations (library choice, hosting, key APIs, edge cases) and capture the agreed spec in ARCHITECTURE.md §3.<n>. The depth of ARCHITECTURE.md is what lets the scaffold skill generate complete working code instead of TODO placeholders. Iterates with the user until they approve both docs. Optionally seeds from a design doc / FRD URL. PRD.md + ARCHITECTURE.md are the source of truth for every downstream skill (generate, build, assemble). Run this BEFORE any code is generated.
日本語の概要は準備中です。原文の説明を表示しています。
Audits existing table permissions on a Power Pages site by analyzing them against site code and Dataverse metadata, then GRADES the configuration with deterministic 1–5 scores across 3 security/usability/correctness categories (9 dimensions). Detection is anchored by a recurring-issue catalog so findings and severities stay consistent run-to-run. Generates an HTML report with an at-a-glance verdict and per-category scores in the Overview plus a single list of **major/minor** issues (each major issue labelled permissions-only or upstream-caused with a short justification), and suggested fixes. Use when the user wants to review, verify, check, score, or grade table permissions for security issues.
日本語の概要は準備中です。原文の説明を表示しています。
Authoritative rules and patterns for production-quality Kotlin Coroutines onto Android. Covers structured concurrency, lifecycle integration, and reactive streams.
日本語の概要は準備中です。原文の説明を表示しています。
Collecting and synthesizing user feedback across channels (support tickets, NPS, in-app feedback, sales calls, social mentions, customer councils) into a continuous signal that informs product decisions. The triage discipline that distinguishes loudest-voice (whoever complains most wins) from averaged-noise (every signal weighted equally) from triaged-synthesis (signal weighted by source quality, frequency, and decision relevance). Triggers on user feedback, customer feedback aggregation, NPS, support ticket analysis, customer councils, feedback synthesis, voice of customer, feedback triage, in-app feedback. Also triggers when feedback channels overflow with volume that does not produce decisions, when the loudest-voice problem is steering roadmap, or when continuous feedback streams need synthesis discipline.
日本語の概要は準備中です。原文の説明を表示しています。
Design forms that convert, validate well, resist spam, and integrate cleanly with downstream systems. Use this skill when designing or auditing any form (contact, signup, checkout, multi-step, embedded), planning validation logic, fighting spam, choosing form tooling, or improving form conversion. Triggers on form design, form validation, form conversion, multi-step form, form spam, captcha, honeypot, form abandonment, signup form, contact form. Also triggers when form completion rates are low or spam is overwhelming.
日本語の概要は準備中です。原文の説明を表示しています。
Audit the brand, UX, and site design of the leading sites in a vertical as a set of observable cross-site patterns, producing the experience bar a new build must meet or beat. Use this skill whenever the user wants to assess the competitive design field, capture vertical conventions, identify the design and UX bar of a category, or set the experience standard before a build. Triggers on competitor experience audit, UX audit, site design audit, brand audit, design conventions, what makes these sites good, vertical conventions, storefront patterns, merchandising patterns, layout density, primary task, design bar, category conventions, retail vs marketing register, what does the field do. Also triggers when an audit of the competitive field has captured technical signals (SEO, accessibility) but never named the brand, UX, or design conventions, and the build downstream will read as off-vertical without that bar.
日本語の概要は準備中です。原文の説明を表示しています。
Turn new AI names or unstructured AI market signals into a keyword priority table. For each name it finds the generic search terms downstream of it, screens them for relevance, and checks novelty, demand size and momentum against Google Ads volume and Google Trends, ending in prioritize, watch or skip. Use when the user has new model, product or repository names (or an AI listening report, a batch of posts, a changelog) and asks which keywords to build pages or tools for. Runs the new-term-radar command line; needs an AISA_API_KEY, and a GOANYAPI_API_KEY improves it.
日本語の概要は準備中です。原文の説明を表示しています。
How a downstream app consumes the shared @kolu/surface stack (@kolu/surface · surface-app · surface-nix-host · surface-mcp) — declaring a typed reactive surface, serving it, consuming it (SolidJS hooks or a CLI), and mirroring a remote surface over ssh. Grounded in the real consumers: kolu, pulam-web, drishti, odu, and the TUIs. Load when wiring a surface server/client/mirror, or reaching for getHostSession / a link / the `.use()` hooks. CHANGING the framework is gated separately — `.claude/rules/surface.md` (a paired, CI-green drishti PR pinned to final kolu HEAD).
日本語の概要は準備中です。原文の説明を表示しています。
Build or change a customer-system integration with explicit data mapping, permissions, retries and reconciliation. Use for connectors, imports, write-back and upstream APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Install an improved variant of one named skill: resolve it by local path, repo, or name, run skill-creator's retrofit on a throwaway copy, then install the improved result. Don't use for improving in place, upstream PRs, or plain asm install.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze event logs, clickstreams, user paths, product funnels, retention, behavioral segments, transition graphs, step matrices, sequence patterns, and customer journeys using Retentioneering. Use when the user provides CSV, Parquet, pandas, or database event data containing user, event, and timestamp columns, or asks why users convert, churn, loop, abandon a flow, or follow particular product paths. Do not use for qualitative journey-mapping workshops or aggregate website traffic without user-level event sequences.
日本語の概要は準備中です。原文の説明を表示しています。
Eng manager-mode plan review. Scope challenge, architecture review, code quality review, detailed test coverage diagram, performance review. Produces test plan artifact for downstream QA. Optional cross-model outside voice.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-AI second opinion via OpenAI Codex CLI. Three modes: Review (pass/fail gate), Challenge (adversarial edge-case finder), Consult (freeform with session continuity). Read-only with streaming output and thinking traces. Cross-model analysis when review has already run.
日本語の概要は準備中です。原文の説明を表示しています。
Builds Next.js 14+ applications with App Router, server components, server actions, middleware, streaming SSR, and Vercel deployment.
日本語の概要は準備中です。原文の説明を表示しています。